How to shape the weights or nodes during gradient training of neural network? Training with constraints?
I have a somewhat similar problem, there's this paper that I was supposed to extend (I can explain how): https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-017-1984-2
What they do is that they have a connection network between input and second layer (giving some biological context to training) I don't know how you can maintain the zero edges during back propagation though.